A parts-based approach for automatic 3D-shape categorization using belief functions

Tabia, Hedi; Daoudi, Mohamed; Vandeborre, Jean Philippe; Colot, Olivier

Type de document :

Compte-rendu et recension critique d'ouvrage

Titre :

A parts-based approach for automatic 3D-shape categorization using belief functions

Auteur(s) :

Tabia, Hedi [Auteur]
LAGIS-SI
Daoudi, Mohamed [Auteur]

Institut TELECOM/TELECOM Lille1
FOX MIIRE [LIFL]
Vandeborre, Jean Philippe [Auteur]

Institut TELECOM/TELECOM Lille1
FOX MIIRE [LIFL]
Colot, Olivier [Auteur]

LAGIS-SI

Titre de la revue :

ACM Transactions on Intelligent Systems and Technology

Pagination :

33:1-33:16

Éditeur :

ACM

Date de publication :

2013-03

ISSN :

2157-6904

Discipline(s) HAL :

Informatique [cs]/Vision par ordinateur et reconnaissance de formes [cs.CV]

Résumé en anglais : [en]

Grouping 3D-objects into (semantically) meaningful categories is a challenging and important problem in 3D-mining and shape processing. Here, we present a novel approach to categorize 3D-objects. The method described in ...
Lire la suite >Grouping 3D-objects into (semantically) meaningful categories is a challenging and important problem in 3D-mining and shape processing. Here, we present a novel approach to categorize 3D-objects. The method described in this paper, is a belief function based approach and consists of two stages. The training stage, where 3D-objects in the same category are processed and a set of representative parts is constructed, and the labeling stage, where unknown objects are categorized. The experimental results obtained on the Tosca- Sumner and the Shrec07 datasets show that the system efficiently performs in categorizing 3D-models.Lire moins >

Langue :

Anglais

Vulgarisation :

Non

Collections :